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A Bayesian Approach to Modelling Graphical Vector Autoregressions

✍ Scribed by Jukka Corander; Mattias Villani


Book ID
111039959
Publisher
John Wiley and Sons
Year
2006
Tongue
English
Weight
256 KB
Volume
27
Category
Article
ISSN
0143-9782

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In this paper, we investigate the properties of Bayes estimators of vector autoregression (VAR) coe cients and the covariance matrix under two commonly employed loss functions. We point out that the posterior mean of the variances of the VAR errors under the Je reys prior is likely to have an over-e